Niels Holm-Nielsen - Head of the Global Facility for Disaster Reduction and Recovery (GFDRR). (LinkedIn|Website)
GFDRR, administered by the World Bank Group, supports low-income countries on disaster risk mititgation. Since 2015, GFDRR has mobilized around $35 billion in financing for disaster and climate resilience operations worldwide, making a significant impact on reducing vulnerability to natural hazards.
Holm-Nielsen joined the World Bank in 2006 and has held key positions in Disaster Risk Management across regions such as Latin America, the Caribbean, and Africa, most recently serving as Lead Disaster Risk Management Specialist and Global Lead for Resilience and Disaster Risk Management.
Recommendation:
It is recommended that Holm-Nielsen significantly increase funding for disaster risk reduction in Southern and Eastern Asia. The regression analysis demonstrates a link between economic damage and progress in risk reduction, suggesting that enhanced efforts can reduce economic losses. Allocating more resources to countries like Nepal, Vietnam, Cambodia, Thailand, Pakistan, and the Philippines will be a strategic investment in sustainable development that improves economic resilience.
Evidence
The analysis focuses on three variables:
Number of people affected by disasters per 100,000 and Total economic damages from disasters as a share of GDP from the Natural Disaster data.
regions_list <-c("Africa", "Asia", "North America", "South America", "Europe", "Oceania")regional_data <- disaster_data %>%filter(Entity %in% regions_list)regional_impact <- regional_data %>%group_by(Entity) %>%summarise(across(c(`EconDmgShare`, `HumanDmgPer`), sum, na.rm =TRUE))plot1 <-ggplot(regional_impact, aes(x = Entity, y =`HumanDmgPer`, fill = Entity)) +geom_bar(stat ="identity", position ="dodge", width =0.75) +labs(title ="Regional Sociological Impact of Natural Disasters (1960 - 2010)", y ="People affected per 100,000", x ="Region") +theme_minimal() +scale_fill_viridis_d(option ="mako") +theme(legend.position ="none")ggplotly(plot1)
Code
plot2 <-ggplot(regional_impact, aes(x = Entity, y =`EconDmgShare`, fill = Entity)) +geom_bar(stat ="identity", position ="dodge", width =0.75) +labs(title ="Regional Economic Damage of Natural Disasters (1960 - 2010)", y ="Economic damage as a share of GDP (%)", x ="Region") +theme_minimal() +scale_fill_viridis_d(option ="mako") +theme(legend.position ="none")ggplotly(plot2)
The bar plots reveal a high disparity in human damage between Asia and the rest of the world. While ranking second to Oceania in economic damage, it is also significant, highlighting Asia’s overwhelming vulnerability to natural disaster and need of damage mitigation and recovery support.
II. High-Risk Zones in Southern and Eastern Asia
Code
# Filter datadmg2010_data <- disaster_data %>%filter(Year ==2010, !is.na(EconDmgShare)) %>%select(Entity, EconDmgShare)map_data <-ne_countries(scale ="medium", returnclass ="sf", continent ="asia")# Merge the cleaned disaster data with the world map datamap_data <- map_data %>%left_join(dmg2010_data, by =c("name"="Entity"))# Mapmy_map <-ggplot(data = map_data) +geom_sf(lwd =0.2, aes(fill = EconDmgShare,text =paste("Country:", name, "<br>Economic Damage:", round(EconDmgShare, 2)))) +scale_fill_viridis(option ="viridis", na.value ="grey50", breaks =seq(0, 2.402, by =0.4)) +labs(title ="Total Economic Damages from Disasters as a Share of GDP by Country in 2010",fill ="Economic\nDmg (%)",x ="Longitude", y ="Latitude") +theme_minimal() +theme(plot.title =element_text(hjust =0.5))ggplotly(my_map, tooltip ="text")
The interactive map, visualizing economic damage across Asian countries, indicates that GFDRR should prioritize resources for countries such as Nepal, Vietnam, Cambodia, Thailand, Pakistan, and the Philippines. This aligns with findings from the ASEAN Disaster Risk Management Initiative (UNDRR 2010), which identifies Southeast Asia as one of the most disaster-prone regions in the world. Given that all these countries are located in Southern and Eastern Asia, there is a strong case for focusing disaster mitigation effort in this vulnerable area.
III. The Case for Investing in Resilience
Code
sea_countries_list <-c("Bangladesh", "Brunei", "Cambodia", "China", "Fiji", "India", "Indonesia", "Japan", "Kiribati", "Laos", "Malaysia", "Myanmar", "Nepal", "North Korea", "Pakistan", "Palau", "Philippines", "Singapore", "South Korea", "Sri Lanka", "Thailand", "Timor", "Tuvalu", "Vietnam")# Join with score data and filterfinal_data <- score_data %>%left_join(dmg2010_data, by =c("country"="Entity")) %>%filter(country %in% sea_countries_list) %>%na.omit()plot3 <-ggplot(final_data, aes(x = EconDmgShare, y = RiskReductionScore)) +geom_point(aes(text =paste("Country: ", country, "<br>Score: ", RiskReductionScore, "<br>Economic Damage: ", round(EconDmgShare, 2)))) +geom_smooth(method ="lm", se =FALSE, color ="#42f5b3") +labs(x ="Economic Damage as a share of GDP (2010)",y ="Risk Reduction Progress Score (2009 - 2011)",title ="Correlation between Risk Reduction Progress Score and Economic Damage") +theme_minimal()ggplotly(plot3, tooltip ="text")
The disaster risk reduction progress score is based on self-assessment scores submitted by countries under the Hyogo Framework (UNDRR) from 2009 to 2011, ranging from 1 to 5. The regression model indicates a moderate negative correlation between economic damage as a share of GDP in 2010 and the score for Southern and Eastern Asian countries. In line with the findings of the Asian Development Bank, which states that effective disaster risk reduction can yield $4–$7 in savings for every dollar invested, supporting the argument for GFDRR to increase funding in these regions
IV. Hypothesis Testing
To determine if economic damages of countries in the Southern and Eastern Asia area is significantly higher than the rest of Asia, a proportion test is utilized.
p-value = 0.02243 < 0.05
The p-value falls below the threshold of 0.05, supporting the conclusion that a greater number of countries in Southern and Eastern Asia experience substantial economic damage.
Niels Holm-Nielsen is a solid choice due to his leading position at GFDRR and extensive experience in disaster risk management. Since 2015, GFDRR has mobilized about $35 billion for disaster and climate resilience initiatives. Holm-Nielsen’s leadership has been crucial to this important work of reducing vulnerability to natural disasters. This report provides Holm-Nielsen with insight on which region the organization should focus on, and how enhancing risk mitigation might benefit a country’s economic growth.
1. Hypotheses
Since around half of Asian countries are in the Southern and Eastern Asia, we expect half of the countries that experienced high economic damage (>0.5% of GDP) to be in the region.
H0:50% of Asian countries that experienced high economic damage from natural disaster are from Southern and Eastern Asia.
H1:More than 50% of Asian countries that experienced high economic damage from natural disaster are from Southern and Eastern Asia.
2. Assumptions
Database Accuracy: All countries’ statistics are correct.
Independence: Countries’ damage should be independent of each other.
prop.test(sea_count, total_count, 0.5, alternative ="greater")
1-sample proportions test with continuity correction
data: sea_count out of total_count, null probability 0.5
X-squared = 4.0238, df = 1, p-value = 0.02243
alternative hypothesis: true p is greater than 0.5
95 percent confidence interval:
0.5280587 1.0000000
sample estimates:
p
0.6666667
5. Conclusion
Reject H0
Data on natural disasters is limited, with only one data point every ten years.
The Natural Disaster database includes records only up to 2010.
Certain countries and territories are unable to provide data.
Ethics Statement
Shared Professional Values: The project follows the shared value of Respect by acknowledging and properly crediting the works of others, ensuring that their work was neither suppressed nor diminished.
Ethical Principles: The project upheld the principle of Bearing Responsibility for the Integrity of the Discipline by ensuring transparency in methods and findings, avoiding any form of deception or misrepresentation.
